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Field
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. The position will focus on developing computational algorithms and tools for the analysis of mass spectrometry-based proteomics data. Research projects will center on advancing the FragPipe computational
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position is available in the group of Prof. Alexey Nesvizhskii at the University of Michigan Medical School. The position will focus on developing computational algorithms and tools for the analysis of mass
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) experience in large model training, knowledge distillation or efficient deep learning algorithm development, foundation model implementation and optimisation; and (c) good communication skills in English
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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and analytics. The post holder will develop new optimisation models and algorithms to support operational and real‑time decision making in disaster response contexts, with the aim of improving resource
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human-centred collaborative robotic systems, with emphasis on embodied intelligence and shared autonomy; (c) develop algorithms for human intention understanding, multimodal perception and fusion and
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numerical simulations of complex dynamic systems, e.g. turbulence, hurricane. The duty of the role is within the range of: 1) developing novel algorithms on data analyses and data mining, e.g. Large Models
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deep learning algorithms to enable robotic arms to perform complex tasks guided by natural language instructions. Experiment with and deploy vision-language-action models on robotic platforms
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on computer vision. The role involves developing and advancing novel algorithms for emerging challenges in computer vision, including continual learning and few-shot learning. The candidate is also expected
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the research on Integrated Sensing and Communications (ISAC) with Reconfigurable Intelligent Metasurfaces (RIS). Key Responsibilities: Design the algorithm for Integrated Sensing and Communications